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The study aims to optimize truck routes by minimizing social and economic costs. It introduces a strategy involving diverse drones and their potential for reusing at DNs based on flight range. In HTDRP-DC, trucks can select and transport various drones to LDs to reduce deprivation time. This study estimates the nonlinear deprivation cost function using a linear two-piece-wise function, leading to MILP formulations. A heuristic-based Benders Decomposition approach is implemented to address medium and large instances. Valid inequalities and a heuristic method enhance convergence boundaries, ensuring an efficient solution methodology.

Research has yet to address critical factors in disaster logistics: minimizing the social and economic costs simultaneously and using drones in relief distribution; deprivation as a social cost measures the human suffering from a shortage of relief supplies. The proposed hybrid truck-drone routing problem minimizing deprivation cost (HTDRP-DC) involves distributing relief supplies to dispersed demand nodes with undamaged (LDs) or damaged (DNs) access roads, utilizing multiple trucks and diverse drones. A Benders Decomposition approach is enhanced by accelerating techniques.

Incorporating deprivation and economic costs results in selecting optimal routes, effectively reducing the time required to assist affected areas. Additionally, employing various drone types and their reuse in damaged nodes reduces deprivation time and associated deprivation costs. The study employs valid inequalities and the heuristic method to solve the master problem, substantially reducing computational time and iterations compared to GAMS and classical Benders Decomposition Algorithm. The proposed heuristic-based Benders Decomposition approach is applied to a disaster in Tehran, demonstrating efficient solutions for the HTDRP-DC regarding computational time and convergence rate.

Current research introduces an HTDRP-DC problem that addresses minimizing deprivation costs considering the vehicle’s arrival time as the deprivation time, offering a unique solution to optimize route selection in relief distribution. Furthermore, integrating heuristic methods and valid inequalities into the Benders Decomposition approach enhances its effectiveness in solving complex routing challenges in disaster scenarios.

The Old Farmer Pension Program (OFPP) represents Taiwan’s long-standing efforts aiming at improving farm household income and well-being; however, how effective the pension program is in terms of achieving the policy agenda has remained unclear. The paper aims to discuss this issue.

Based on data drawn from the Survey of Family Income and Expenditure during 1999–2013, two identification strategies are used to examine the effect of OFPP. First the authors apply the Blinder-Oaxaca decomposition to address the concern if the program reaches the socially/economically disadvantaged farm households. The second identification strategy involves using the static and dynamic decomposition approaches to identify the major factors contributing to farm household income inequality and the redistribution role of the OFPP.

Results from the Blinder-Oaxaca decomposition indicate that about 60 percent of the income gap can be eliminated if the pension recipients’ socio-economic characteristics are the same as the non-recipient group, suggesting it is the disadvantaged group that receives the old farmer pension. Moreover, the results suggest the significant contributions of household investments in health and human capital as well as diversification toward nonfarm activities, to income inequality among Taiwan’s farm households. Results from the dynamic decomposition suggest that the first-wave adjustment of the OFPP enlarges farm household income inequality, the following two waves of adjustment, however, plays an equalizing role.

This study adds to the literature by providing a methodological refinement promoting the view that it calls for the use of the dynamic (change) decomposition framework to investigate the inequality-enlarging or inequality-equalizing role each income determinant plays.

Suggests that, in recent years, remarkable progress has been made in the development of the topological design of logistics networks, especially in the warehouse location problem. Extends the standard warehouse location problem to a generalization of multiproduct capacitated warehouse location problem, as opposed to differentiated variations of a single‐product warehouse location problem, where each warehouse has a given capacity for carrying each product. Presents an algorithm based on cross‐decomposition, to reduce the computational difficulty by incorporating Benders decomposition and Lagrangean relaxation. Computational results of this algorithm are encouraging.

The purpose of this paper is to propose a model for allocating resources in various zones after a large-scale disaster. This study is motivated by the social dissatisfaction caused by inefficient relief distribution.

This study introduces an agent-based model (ABM) framework for integrating stakeholders’ interests. The proposed model uses the TOPSIS method to create a hierarchy of demand points for qualitative and quantitative parameters. A decomposition algorithm has been proposed to solve fleet allocation.

Relief distribution based on the urgency of demand points increases social benefit. A decomposition approach generates higher social benefit than the enumeration approach. The transportation cost is lower in the enumeration approach.

This study does not consider fleet contracts explicitly, but rather assumes a linear cost function for computing transportation costs.

The outcomes of this study can be a valuable tool for relief distribution planning. This model may also help reduce the social dissatisfaction caused by ad hoc relief distribution.

This study introduces an ABM for humanitarian logistics, proposes a decomposition approach, and explores the ontology of stakeholders of humanitarian logistics specific to last-mile distribution.

The need to measure organisational effectiveness has become increasingly accepted. Performance measurements can readily be developed but need to be further defined as performance metrics. The paper's aim is to show how the use of the decomposition technique enables the development of electronic commerce (e‐commerce) metrics.

In the approach to value decomposition, value constructs are identified at the highest level, decomposed into the next levels, referred to as value variables, which are further broken down into value metrics. During decomposition, proper splicing has to occur. This implies that values (constructs, variables and metrics) should be carefully specified and that their interconnections should be controlled. Furthermore, functional integrity is required so that a succinct statement can be made for each metric.

The paper identified value constructs and value variables for six e‐commerce applications. They are aggregated into corporate performance management measures so that the various lower level value metrics can be made to work seamlessly together.

Although there is large agreement on the key values obtained from e‐commerce, it is difficult to achieve the degree of integrity required by the decomposition technique. Further research is required.

Performance measures provide a factual representation of important business activities and enable greater preciseness in their execution. The paper provides insight into values and associated measures in important activities of e‐commerce, namely VRM, B2C, B2B, CRM, EP, and ERP.

This paper aims to deal with integrated planning and scheduling problem in multi-site manufacturing environment and provides a comprehensive review of literature. Classification schemes and various aspects of planning and scheduling problem in multi-site manufacturing are highlighted.

A structured review methodology is adopted to classify the relevant literature. Taxonomy for classification of the problem is presented, followed by review of modelling approaches, solution strategies and challenges faced in multi-site integrated planning and scheduling problem.

The paper is concluded with interesting research findings and a short view on directions related to modelling approach, solution strategy and technique for further developments in the area of multi-site integrated planning and scheduling.

The findings of this study would be helpful for future researchers and practitioners to provide a knowledge base and to further work in this area.

This study attempts to consolidate the diverse literature available and highlight the various aspects of planning and scheduling in multi-site manufacturing.

Previous studies have found significant differences in consumer attitudes toward marketing between countries and attributed such variations to differences in the stage of consumerism development and cultural values. This study aims to test these competing hypotheses using econometric decomposition to identify the source of such cross‐country variations.

Using survey data of consumer attitudes toward marketing from China and Canada, this study adopts econometric decomposition to examine the cross‐country difference in consumer attitudes toward marketing.

The results show that Chinese consumers have more positive attitudes toward marketing than Canadians and the two countries differ significantly across all predictor variables. However, the results of decomposition suggest that consumerism, individualism and relativism do not have any significant effect on the country gap in consumer attitudes toward marketing, while idealism has a significant coefficient effect.

The study finds different effects of cultural values on consumer attitudes across countries and has meaningful implications for international marketing strategies.

The study investigates the sources of cross‐national differences in consumer attitudes toward marketing using rigorous analyses to improve the accuracy of cultural attribution for international marketing and cross‐cultural consumer research.

Performance measurement and management (PMM) is a key practice to drive modern businesses. The literature available in this field highlights a certain maturity regarding performance measurement systems, while few frameworks have been proposed for PMM, which is today's target. Hence this paper aims to focus on the development of a new framework for providing direction and guidance to an organization in measuring and managing its performance.

The proposed framework is developed based on the strengths of the axiomatic design (AD) and the analytical hierarchy process (AHP) techniques.

The framework proposed, namely “Business System Design Decomposition” (BSDD), offers a holistic approach to PMM, identifies cause‐effect relationships in business processes, measures performance versus stakeholders, and offers interlinking between performance indicators. The result is a deep understanding of the business environment and a real step forward for PMM.

The proposed framework for PMM needs to be validated through an empirical approach or by a clinical approach utilizing a case study.

The paper offers to academics, managers and practitioners a framework to understand, measure and manage business performance. Moreover, the application of the framework represents a learning process for the people involved in the project.

Little research is available regarding holistic performance measurement and management systems and the understanding of quantitative relations between performance indicators. By combining two existing methodologies, the framework proposed adds value to the existing body of knowledge and offers good insights for addressing future research.